Self-driving cars can still be fooled by tampered-with signsSimple stickers can effectively mislead self-driving cars into making incorrect decisions.
Adaptive Attacks Expose SLM Vulnerabilities and Qualitative Insights | HackerNoonDefense mechanisms can enhance robustness against adversarial attacks, but attackers can still succeed with larger budgets.
Unified Speech and Language Models Can Be Vulnerable to Adversarial Attacks | HackerNoonIntegrated Speech and Large Language Models are vulnerable to adversarial attacks, necessitating robust countermeasures for enhanced security.
Transfer Attacks Reveal SLM Vulnerabilities and Effective Noise Defenses | HackerNoonFlanT5-based models are more resistant to cross-model attacks, illustrating their robustness compared to other architectures.
Adaptive Attacks Expose SLM Vulnerabilities and Qualitative Insights | HackerNoonDefense mechanisms can enhance robustness against adversarial attacks, but attackers can still succeed with larger budgets.
Unified Speech and Language Models Can Be Vulnerable to Adversarial Attacks | HackerNoonIntegrated Speech and Large Language Models are vulnerable to adversarial attacks, necessitating robust countermeasures for enhanced security.
Transfer Attacks Reveal SLM Vulnerabilities and Effective Noise Defenses | HackerNoonFlanT5-based models are more resistant to cross-model attacks, illustrating their robustness compared to other architectures.
Why Cybercriminals Are Not Necessarily Embracing AI | HackerNoonAI aids malware detection but also introduces new cyber threats, demonstrated by threat actors using tools like ChatGPT.
Adversarial Attacks Challenge the Integrity of Speech Language Models | HackerNoonAdversarial attacks can significantly compromise Spoken QA systems, necessitating robust defense mechanisms.
Why Cybercriminals Are Not Necessarily Embracing AI | HackerNoonAI aids malware detection but also introduces new cyber threats, demonstrated by threat actors using tools like ChatGPT.
Adversarial Attacks Challenge the Integrity of Speech Language Models | HackerNoonAdversarial attacks can significantly compromise Spoken QA systems, necessitating robust defense mechanisms.
Integrated Speech Language Models Face Critical Safety Vulnerabilities | HackerNoonThe study examines the safety alignment of speech language models against adversarial attacks.
Datasets and Evaluation Define the Robustness of Speech Language Models | HackerNoonThe article discusses the methods and datasets used for training and evaluating speech-language models (SLMs) against adversarial attacks.
OpenAI Presents Research on Inference-Time Compute to Better AI SecurityMore inference-time compute reduces AI models' vulnerability to adversarial attacks.
Certain names make ChatGPT grind to a halt, and we know whyHard-coded filters can inadvertently disrupt usability and functionality in AI interactions, particularly for common names.AI tools face challenges from adversarial attacks that exploit system vulnerabilities, requiring ongoing evaluation and adjustment.
Pentagon launches plan to keep its AI-powered tech from being hijackedAI systems vulnerable to adversarial attacks with visual 'noise' patches.Pentagon's GARD program works on identifying and defending against such vulnerabilities.
Can AI Be Superhuman? Flaws in Top Gaming Bot Cast DoubtSuperhuman AI systems, like bots playing Go, can have vulnerabilities impacting safety and reliability.